Astera

FEBRUARY 14, 2024

Data Vault 101: Your Guide to Adaptable and Scalable Data Warehousing As businesses deal with larger and more diverse volumes of data, managing that data has become increasingly difficult. Scalability As the healthcare providers grow or add more source systems, data vault scales easily.

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Astera

DECEMBER 16, 2022

John Stillwagen, Senior Director MIS at La Jolla Institute for Immunology, demonstrated how efficiently our data warehouse solution, Astera Data Warehouse Builder, helps you build an enterprise-grade data warehouse via a no-code interface. Big Data LDN 2022 | Olympia, London. Final Word. Stay tuned!

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Astera

NOVEMBER 30, 2023

With rising data volumes, dynamic modeling requirements, and the need for improved operational efficiency, enterprises must equip themselves with smart solutions for efficient data management and analysis. This is where Data Vault 2.0 It supersedes Data Vault 1.0, What’s New in Data Vault 2.0? Data Vault 2.0

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Astera

JANUARY 19, 2024

Shortcomings in Complete Data Management : While MuleSoft excels in integration and connectivity, it falls short of being an end-to-end data management platform. Notably, MuleSoft lacks built-in capabilities for AI-powered data extraction and the direct construction of data warehouses.

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Astera

JUNE 6, 2023

The pipeline includes stages such as data ingestion, extraction, transformation, validation, storage, analysis, and delivery. Technologies like ETL, batch processing, real-time streaming, and data warehouses are used. They are ideal for handling historical data analysis, offline reporting, and batch-oriented tasks.

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Astera

MAY 9, 2023

Data processing involves transforming raw data into valuable information for businesses. Generally, data scientists process data, which includes collecting, organizing, cleaning, verifying, analyzing, and converting it into readable formats such as graphs or documents. Try it Now!

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Astera

JUNE 13, 2023

The ETL process involves extracting data from various sources and transforming it into a structured format suitable for analysis. Finally, it involves loading it into a data warehouse or any other type of destination. Transformation: Data is cleaned, filtered, and manipulated to ensure quality and consistency.

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Astera

JUNE 13, 2023

The ETL process involves extracting data from various sources and transforming it into a structured format suitable for analysis. Finally, it involves loading it into a data warehouse or any other type of destination. Transformation: Data is cleaned, filtered, and manipulated to ensure quality and consistency.

Data Warehouse 52

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Astera

JUNE 13, 2023

The ETL process involves extracting data from various sources and transforming it into a structured format suitable for analysis. Finally, it involves loading it into a data warehouse or any other type of destination. Transformation: Data is cleaned, filtered, and manipulated to ensure quality and consistency.

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Astera

JANUARY 24, 2024

What is Change Data Capture? Change Data Capture (CDC) is a technique used in data management to identify and track changes made to data in a database, and applying those changes to the target system. Below is the step-by-step explanation on how change data capture typically works.

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Astera

DECEMBER 29, 2023

Among the key players in this domain is Microsoft, with its extensive line of products and services, including SQL Server data warehouse. In this article, we’re going to talk about Microsoft’s SQL Server-based data warehouse in detail, but first, let’s quickly get the basics out of the way.

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Astera

DECEMBER 29, 2023

Among the key players in this domain is Microsoft, with its extensive line of products and services, including SQL Server data warehouse. In this article, we’re going to talk about Microsoft’s SQL Server-based data warehouse in detail, but first, let’s quickly get the basics out of the way.

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Astera

DECEMBER 21, 2022

A voluminous increase in unstructured data has made data management and data extraction challenging. The data needs to be converted into machine-readable formats for analysis. However, the growing importance of data-driven decisions has changed how managers make strategic choices. Data Mining.

Data Mining 52

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Astera

OCTOBER 31, 2023

Enhancing Data Consumption Data preparation makes data more consumable by providing metadata and documentation that ensure transparency and usability. It also shares data through APIs, web services, files, or databases, making it accessible to diverse users and applications. Timeliness.

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Astera

OCTOBER 27, 2023

What is a Cloud Data Warehouse? Simply put, a cloud data warehouse is a data warehouse that exists in the cloud environment, capable of combining exabytes of data from multiple sources. A cloud data warehouse is critical to make quick, data-driven decisions.

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Argon Digital

AUGUST 11, 2022

While not every business or agency has quite this level of document management overhead, dealing with paper forms and disorganized electronic documents costs time, money, risk, and employee burnout. From a metal cabinet to digital document management. Modern content management features.

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Astera

APRIL 23, 2024

Data quality metrics are not just a technical concern; they directly impact a business’s bottom line. million annually due to low-quality data. Furthermore: 41% of data warehouse projects are unsuccessful, primarily because of insufficient data quality.

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Astera

NOVEMBER 27, 2023

Here are some of the distinct advantages of data profiling: Informed Decision-Making: Data profiling provides a clear understanding of the available data, its quality, and its structure.

Data Mining 52

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Sisense

MARCH 20, 2019

MongoDB (or NoSQL) : An open source Database Management System (DBMS), MongoDB uses a document-oriented database model. That means that instead of using tables in rows in a database, MongoDB is made up of collections of documents. Data Warehousing. Hadoop : This is the main framework for processing Big Data.

Big Data 72

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Astera

APRIL 24, 2024

There are different types of data ingestion tools, each catering to the specific aspect of data handling. Standalone Data Ingestion Tools : These focus on efficiently capturing and delivering data to target systems like data lakes and data warehouses.

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Astera

MARCH 11, 2024

It eliminates the need for complex infrastructure management, resulting in streamlined operations. According to a recent Gartner survey, 85% of enterprises now use cloud-based data warehouses like Snowflake for their analytics needs. What are Snowflake ETL Tools? Snowflake ETL tools are not a specific category of ETL tools.

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Actian

JANUARY 25, 2019

The event was an incredible opportunity for knowledge-sharing among industry leaders – swapping insights and predictions on data management and analytics, hybrid data, operational data warehouses and more. Keep an eye out for updates on 2019 events in the pipeline! Actian Zen Core Database for Android.

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Astera

MARCH 20, 2024

This article covers everything about enterprise data management, including its definition, components, comparison with master data management, benefits, and best practices. What Is Enterprise Data Management (EDM)? Why is Enterprise Data Management Important?

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Astera

JANUARY 2, 2024

Relying on this data to power business decisions is like setting sail without a map. This is why organizations have effective data management in place. But what exactly is data management? What Is Data Management? As businesses evolve, so does their data.

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Astera

JULY 18, 2023

Scalability : The best part about data wrangling tools is their ability to handle large data volumes, allowing seamless scalability. These tools employ optimized algorithms and parallel processing techniques, enabling faster data processing and analysis. The tool can save you countless hours of manual work.

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Astera

FEBRUARY 27, 2024

52% of IT experts consider faster analytics essential to data warehouse success. However, scaling your data warehouse and optimizing performance becomes more difficult as data volume grows. Leveraging data warehouse best practices can help you design, build, and manage data warehouses more effectively.

Data Warehouse 52

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Astera

FEBRUARY 27, 2024

52% of IT experts consider faster analytics essential to data warehouse success. However, scaling your data warehouse and optimizing performance becomes more difficult as data volume grows. Leveraging data warehouse best practices can help you design, build, and manage data warehouses more effectively.

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Smart Data Collective

SEPTEMBER 26, 2021

There’s not much value in holding on to raw data without putting it to good use, yet as the cost of storage continues to decrease, organizations find it useful to collect raw data for additional processing. The raw data can be fed into a database or data warehouse. The central concept is the idea of a document.

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Business Analysis Knowledge Share

OCTOBER 24, 2023

This article aims to provide a comprehensive overview of Data Warehousing, breaking down key concepts that every Business Analyst should know. Introduction As businesses generate and accumulate vast amounts of data, the need for efficient data management and analysis becomes paramount.

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Astera

DECEMBER 16, 2022

These large data volumes present numerous data management challenges for companies, especially those with outdated management systems. Let’s explore the 7 data management challenges that tech companies face and how to overcome them. Data Management Challenges. See Case Sudy.

Data Management 52

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Astera

DECEMBER 16, 2022

These large data volumes present numerous data management challenges for companies, especially those with outdated management systems. Let’s explore the 7 data management challenges that tech companies face and how to overcome them. Data Management Challenges. See Case Sudy.

Data Management 52

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Astera

MAY 14, 2024

Process metadata: tracks data handling steps. It ensures data quality and reproducibility by documenting how the data was derived and transformed, including its origin. Examples include actions (such as data cleaning steps), tools used, tests performed, and lineage (data source).

Government 52

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Astera

DECEMBER 2, 2022

These large data volumes present numerous challenges for companies, especially those with outdated data management systems. Let’s explore the 7 data management challenges that tech companies face and how to overcome them. Data Management Challenges. Challenge#1: Accessing organizational data.

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BizAcuity

APRIL 1, 2023

So to achieve the benefits of consolidation, Company B’s billing system must be integrated into Company A’s billing system which can be easily done by Informatica Informatica tool for Data Warehousing: Companies establishing their warehouses of data will need ETL to transfer the data to the warehouse from the Production system.

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Astera

JANUARY 17, 2024

The transformation process may involve the restructuring, cleaning, and formatting of data to align it with the standards and requirements of the intended target system or data warehouse. This phase ensures data consistency, quality, and compatibility.

Real-time Data 52

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Astera

DECEMBER 28, 2023

Airbyte vs Fivetran vs Astera: Overview Airbyte Finally, Airbyte is primarily an open-source data replication solution that leverages ELT to replicate data between applications, APIs, data warehouses, and data lakes. Like other data integration platforms , Airbyte features a visual UI with built-in connectors.

Data Warehouse 52

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Astera

DECEMBER 28, 2023

Airbyte vs Fivetran vs Astera: Overview Airbyte Finally, Airbyte is primarily an open-source data replication solution that leverages ELT to replicate data between applications, APIs, data warehouses, and data lakes. Like other data integration platforms , Airbyte features a visual UI with built-in connectors.

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